Evaluation of the Frequency and Severity of Sleep Abnormalities in Patients with Parkinson s Disease (PD)
Abstract
Over 6 million people worldwide, including one million in the United States, suffer from Parkinson s disease (PD). According to the International Parkinson and Movement Disorder Society, the prevalence of diagnosed patients with the disease will likely double from 2010 to 2040 due to increased life expectancy. Sleep-related symptoms are one of the most common non-motor symptoms in PD. They have been associated with increased risk of neurodegeneration, cognitive decline, and reduced quality of life. To date, the "gold standard" evaluation of sleep disorders is polysomnographic monitoring (PSG). PSG consists of measuring brain activity, eye movements, muscle activity, respiratory status, and electrocardiography (EEG) activity, while the person sleeps over-night in a laboratory setting. However, PSG is cumbersome, expensive, and often does not reflect everyday life conditions. The proposed work relates to specifically to the "sleep biology in Parkinson s disease" call. In the current project, we propose to use novel wireless skin electrodes and wearable sensors to provide a "home-based PSG test." The novel electrodes (now produced by Xtrodes, Ltd.) are printed on a thin and soft sticker, which can be conveniently placed on the face of the person and enable several physiologic recordings over multiple nights in the home environment. Subjects will also wear a wireless wearable sensor on the lower back to assess nocturnal movements. The study will evaluate 240 subjects; 90 individuals at risk, 120 patients with PD, and 30 healthy age matched controls, recruited from the Tel-Aviv Medical Center. Data will be collected over 7 nights in the person s home. The collected data will be used to detect sleep architecture including sleep cycles and sleep disorders. More specifically, we intend to: (1) Assess the frequency, severity, and types of sleep disorders in patients with PD that can be serve as markers of disease progression; (2) Explore changes in sleep architecture and unique patterns of sleep in individuals at risk for developing PD due to known genetic factors that could be used as markers of disease; (3) Use machine learning techniques to identify classifiers of sleep measures indicative of disease characteristics, severity and progression; and (4) Assess the association between sleep disorders, disease severity, autonomic, cognitive function, and medication. Data collected will offer unparalleled information on habitual sleep disorders and their consistency. This information will be combined with additional clinical, genetic, and biological information to provide models for predicting the trajectory or overall pathogenesis of disease, possibly shedding new insights about the neurodegenerative process itself. In addition, assessment and quantification of sleep disorder will enable providers to give adequate care that in turn could help alter this trajectory. If successful, the results of this study will enable to advance precision, personalized medicine, which has the potential to mitigate disease progression.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 10, 2021
- Source ID
- W81XWH2010468
Entities
People
- Anat Mirelman
Organizations
- Tel Aviv Sourasky Medical Center
- United States Army